A Hidden Markov Model (HMM) is a statistical model that represents systems with hidden states through observable events, making it ideal for sequence prediction and time series analysis. It is widely used in fields like speech recognition, bioinformatics, and finance due to its ability to model temporal data and capture the probabilistic relationships between observed and hidden states.