Using "reward" or say supervised training is easier and (near certainly) often gives better result, but unsupervised is more interesting as a research result, it tells that we can actually extract very high level information from data itself, using some "obvious" rules (such as linearly mix adjacent pixels and give as sparse-"laplace distribution like" results as possible). It is important because it proves that we may simulate brain functionality without knowing exact structure of brain (as we know brain is complex), but by analysis the data it processes using lots of simple structure instead.