Bilateral Filtering is an image processing technique used to reduce noise while preserving edges. It works by averaging the pixels in a neighborhood, but it gives more weight to pixels that are similar in color and close in spatial distance. This helps maintain sharp edges in images, making it useful for tasks like photo enhancement and computer vision. The method combines two Gaussian filters: one for spatial distance and another for intensity difference. By balancing these two aspects, Bilateral Filtering effectively smooths out unwanted variations without blurring important features, making it a popular choice in various applications, including image editing and machine learning.