Adopting Nature inspired optimization algorithms for image processing is on the double growth in the last decade. Artificial Bee Colony (ABC) approach is highly potential nature inspired optimization method mimics the bee’s foraging behaviour. Moreover, the popularity of classification and artificial intelligence in different fields leads to the employment of ABC algorithm in upsurge. Notably, Early detection of breast cancer through digital mammogram images is essential as it is the one the most common cause of humankind cancer deaths. the aim of this comprehensive survey was to methodically analyse the effectiveness of using ABC algorithm in medical image enhancement, segmentation, and classification. This study firstly gives introduction of ABC algorithm and its basic mathematical and biological principles and operations respectively. Furthermore, this academic study summarizes the ABC applications on image segmentation techniques like Otsu and image classification approaches like Artificial Neural Networks (ANN). Finally, this far-reaching study come up with the challenges while exercising ABC algorithm in medical image processing, especially in mammogram images.