A bounding box is a rectangular box that is used to define the spatial extent of an object within a digital image or a 3D space. It is commonly used in computer vision and image processing to help identify and locate objects, such as cars, people, or animals. The bounding box is typically represented by the coordinates of its corners, which indicate the position and size of the object. In machine learning, particularly in tasks like object detection, bounding boxes are essential for training algorithms to recognize and classify objects. By providing labeled images with bounding boxes, models learn to predict the location and category of objects in new images. This technique is widely applied in various fields, including autonomous vehicles and surveillance systems.