SIFT, or the Scale-Invariant Feature Transform, is a computer vision algorithm used to detect and describe local features in images. It identifies key points in an image that are robust to changes in scale, rotation, and lighting, making it useful for various applications like object recognition and image stitching. The SIFT algorithm works in several steps, including scale-space extrema detection, keypoint localization, orientation assignment, and descriptor generation. By creating unique descriptors for each keypoint, SIFT allows for effective matching between different images, even if they are taken from different perspectives or under varying conditions.