A Markov chain is a mathematical system that undergoes transitions from one state to another within a finite set of states. The key feature of a Markov chain is that the next state depends only on the current state and not on the sequence of events that preceded it. This property is known as the Markov property. Markov chains are widely used in various fields, including statistics, economics, and computer science. They can model random processes, such as predicting weather patterns or analyzing stock market trends, by representing different states and the probabilities of moving between them.