If you're already used to Matlab, then you may not find my comments as relevant.
If you were already proficient in both, then they're both interchangeable for many tasks (which is in fact why I always recommend learning R over learning Matlab).
Licensing isn't just a minor thing - getting Matlab to run on non-Debian Linux is a painful ordeal. I never actually got it working, because I never bothered to debug its cryptic error messages, and since it's distributed as a precompiled binary, I wasn't going to sit around trying to patch it. A corollary is that R is easier to integrate into other toolkits, and there are a ridiculous number of freely available R libraries that make your life easier.
My issues with Matlab may be things that someone familiar with the language would care less about. That said, I find Matlab to be incredibly, incredibly irritating, and I think that's because it's design is tailored towards people with minimal experience with other programming languages (like research scientists), whereas R's design is simply based off of S - so I find it violates the Principle of Least Surprise less. Matlab is not like Lisp or Haskell (where the journey of understanding the language is valuable in itself) - it's really just a means to an end (number crunching), so the POLS is especally important.
R, unlike Matlab, imposes almost no restrictions on the structure of a program. The
way I see it, Matlab makes Java's broken one-class-per-file model even worse, by imposing more filesystem-level restrictions on my program.
R, unlike Matlab, uses a type system that's more familiar to someone used to programming with multiple datatypes, as opposed to someone used to thinking in terms of strictly numerical structures. I never got the hang of when I should index with () or {} or [] Matlab ... I'd have to look it up to tell you. R, on the other hand, is more like Python in this regard - even if it's not quite as clean as Python, it makes basic things like importing/maniplating CSVs much easier than Python (or even Excel, which is even designed around that exact purpose).
R, unlike Matlab, returns the last value computed, not the last values with the same local names as the return value names.
R, unlike Matlab, uses a more intuitive (to me) definition of dimensions (and of row- vs. column-vectors). I spent 80% of my time in Matlab figuring out how to get dimensions to match in a robust manner, and I've never had to do that in R.
You get the idea - my frustrations with the language itself are mostly with the fact that it's so unlike most other languages, and it's too much of a hassle to learn. My frustrations with the language environment is that the free alternative (R) is much easier to work with, and much more cross-platform.