In today’s world, email has become a massively essential medium of communication, having a near-instant worldwide reach. However, due to its ubiquity, email has also became a highly adopted vehicle for a range of perpetrators to carry out their sinister objectives through ever increasing spamming. Due to the rising severity of the situation, number of researchers, governments and corporations had to adopt a more profound approach, resulting in the establishment of a number of government regulations and scientific research being taking place, especially in recent times. In parallel, the growth in Machine Learning frameworks have also seen a significant rise over the years, which, now days, is having a
prominent footprint in all sorts of developments where Artificial Intelligence may have a say. The issue of spam identification and classification has also been benefited from this evolution. This paper discusses the type and threat of spam emails in detail, and surveys a large number of recent advancements in spam email detection and prevention, particularly focusing on the Machine Learning based spam filtering frameworks. In light of the studies discussed here, a set of gaps in the relevant research initiatives has also been identified.