The Markov Property is a fundamental concept in probability theory and statistics. It states that the future state of a process depends only on its current state, not on the sequence of events that preceded it. This means that if you know the present state, you can predict the future without needing to consider the past. This property is a key feature of Markov Chains, which are mathematical systems that transition from one state to another. In applications like finance, weather forecasting, and game theory, the Markov Property simplifies analysis by allowing predictions based solely on the current situation.