Recurrent Neural Networks (RNNs) are a type of artificial neural network designed to recognize patterns in sequences of data, such as time series, text, or speech. Unlike traditional neural networks, which assume that all inputs are independent of each other, RNNs leverage their architecture to maintain a 'memory' of previous inputs, making them uniquely suited for tasks where context and sequence matter.