Markov Models are mathematical frameworks used to model systems that transition from one state to another, where the probability of each future state depends only on the current state and not on the sequence of events that preceded it. They are widely used in various fields such as economics, genetics, and computer science for modeling random processes and decision-making under uncertainty.