A Recurrent Neural Network (RNN) is a type of artificial intelligence model designed to process sequences of data. Unlike traditional neural networks, RNNs have loops that allow information to be passed from one step of the sequence to the next. This makes them particularly useful for tasks involving time series data, such as predicting stock prices or generating text, where the order of the data matters. RNNs are commonly used in applications like natural language processing, where they can understand the context of words in a sentence. By remembering previous inputs, RNNs can generate more coherent and contextually relevant outputs, making them essential for technologies like chatbots and language translation systems.