The rapid growth in social media as the first point of reference for the latest news and information has made the proliferation of fake news on social media platforms a persistent issue that has significant consequences for brands. Fake news often preys on human beings’ emotions and biases, with the ability to spread rapidly. The spread of misinformation can lead to reputational damage, create uncertainty, and lead to psychiatric illness. Humans are unable to distinguish between real and fake news online instantaneously. Machine learning has emerged as a promising tool for detecting fake news online because it can analyse large amounts of data and identify trends or patterns that are indicative of misleading information. Thus, the use of machine learning techniques can aid in the detection of fake news on social media. This paper is a systematic literature review on machine learning techniques that can detect fake news on social media.