Markovian Approximation is a technique used to simplify complex stochastic processes by assuming that the future state depends only on the current state, not the sequence of events that preceded it. This assumption enables easier mathematical modeling and analysis by reducing the dimensionality of the problem, often at the cost of some accuracy in representing the original system's dynamics.