Recurrent Neural Networks (RNNs) are a type of neural network that is designed to handle sequential data, such as time series data, natural language text, and speech. RNNs have a feedback loop that allows information from previous time steps to be used in the current time step. However, RNNs have a problem called the vanishing gradient problem, which makes it difficult for the network to learn long-term dependencies.