Backpropagation through time (BPTT) is an extension of the backpropagation algorithm for training recurrent neural networks (RNNs) by unfolding them over time and applying backpropagation to the unfolded network. It efficiently computes gradients for sequences by considering the temporal dependencies, making it essential for tasks involving sequential data like language processing and time series prediction.