Scale Invariant Feature Transform (SIFT) is an algorithm used in computer vision to detect and describe local features in images, allowing for robust object recognition even under changes in scale, rotation, and illumination. It works by identifying keypoints and computing descriptors that are invariant to image transformations, making it highly effective for tasks like image matching and object tracking.