Semantic Segmentation is a computer vision task that involves classifying each pixel in an image into predefined categories. This process allows machines to understand the content of an image at a detailed level, distinguishing between different objects and regions, such as cars, trees, and people. By assigning a label to every pixel, Semantic Segmentation enables applications like autonomous driving, where understanding the environment is crucial. It helps in creating more accurate models for tasks such as scene understanding, image editing, and medical imaging, enhancing the ability to analyze and interpret visual data effectively.