I don't know. I think backprop is probably utilized a lot in biological networks. Isn't that why we take tests in school? Obviously backprop doesn't make sense in an unsupervised setting. There's no label to backprop on. But here's an example: I see a stove eye is black when cold, then when I see it turn red, I touch it. Ow, it hurts. That's supervised learning. Don't touch things that are glowing red when they don't…
I think Unsupervised Learning is fundamentally connected with the mission/goal of the AI. Whatever the mission is give to AI, it need to start learning information landscape by itself and make classification and use that knowledge to make predictions and act accordingly to optimized the outcome of the mission its given.
Take self-driving cars as an example. Do you not think that any AI that will be able to do this will be essentially 'given' a huge set of knowledge before it's expected to learn anything by itself?