Back propagation is a learning technique that adjusts weights in the neural network by propagating weight changes:

Correct option is B

Backpropagation is a supervised learning algorithm used in training artificial neural networks. It works by calculating the gradient of the loss function with respect to each weight through the chain rule, propagating these gradients backward from the output layer (sink) to the input layer (source) to adjust the weights and minimize the error.