Long Short-Term Memory, or LSTM, is a special kind of neural network architecture mainly used for temporal or sequence data. It is a type of recurrent neural network (RNN) known for its ability to maintain a constant error that can be back-propagated through time and layers. LSTMs are effective in tasks such as language modeling or generating sequences because they can store and retrieve data over extended periods, unlike standard RNNs which might suffer from the vanishing gradient problem.