Recurrent Neural Networks (RNNs) are neural networks that are used to process sequential data. They are particularly useful in tasks such as natural language processing and speech recognition, as they are able to remember important information from previous inputs. RNNs utilize a type of memory called a recurrent unit, which allows them to store and process information over time. This allows them to learn patterns in sequential data, making them powerful tools for analyzing and predicting time series data.