Monte Carlo Integration is a statistical method used to estimate the value of an integral, particularly in high-dimensional spaces. It relies on random sampling to approximate the area under a curve or the volume of a shape. By generating random points within a defined space and determining how many fall under the curve, one can calculate the integral's value based on the ratio of points inside to the total number of points. This technique is especially useful when dealing with complex functions or multidimensional integrals that are difficult to solve analytically. Monte Carlo Integration is widely applied in fields such as finance, physics, and engineering for simulations and probabilistic modeling.