Backpropagation requires a known, desired output for each input value in order to calculate the loss function gradient. It is therefore usually considered to be a supervised learning method, although it is also used in some unsupervised networks such as autoencoders. It is a generalization of the delta rule to multi-layered feedforward networks, m...
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http://en.wikipedia.org/wiki/Backpropagation
An algorithm for efficiently calculating the error gradient of a neural network, which can then be used as the basis of learning. Backpropagation is equivalent to the delta rule for perceptrons, but can also calculate appropriate weight changes for the hidden layer weights of a multilayer perceptron by generalizing the notion of an error correction...
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http://www.encyclo.co.uk/local/20090
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