The Kolmogorov Backward Equations describe the evolution of expected values of functions of a Markov process over time, providing a powerful tool for predicting future states based on current conditions. They are integral to stochastic calculus and are used extensively in fields like finance and physics to model systems where future states are dependent on both current state and time dynamics.