Bidirectional LSTM (Long Short-Term Memory) is a type of recurrent neural network architecture that processes data in both forward and backward directions, capturing information from both past and future contexts in a sequence. This dual processing capability enhances the model's understanding of temporal dependencies, making it particularly effective for tasks like language modeling and speech recognition.