This paper is actually more interesting: it automatically learns some "neuron" which its firing represents a detected face, without any supervise technique. It shows the possibility to extract complex information solely from data.

Is there any concept of "reward" for this thing?

Wouldn't that make training it much quicker and make it much more accurate?

Or are we trying to avoid any human interaction at all with the earning loop?

See, for example this company (one of many) that trains bees to smell certain odours.

(http://www.inscentinel.com/)

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.