Fake news is a major threat to democracy (e.g., influencing public opinion), and its impact cannot be understated particularly in our current socially and digitally connected society. The research community from different disciplines (e.g., computer science, political science, information science, and linguistics) have also studied the dissemination, detection and mitigation of fake news, however it remains challenging to detect and prevent the dissemination of fake news in practice. With AI powered systems, its highly crucial to understand the detector's decision of fake news by means of proper user-friendly explanations when it comes to social media. Hence, in this paper, we systematically survey existing state-of-the-art approaches designed to detect and mitigate the dissemination of fake news, and based on the analysis, we discuss several key challenges and present potential future research agenda specially incorporating AI explainable Fake news credibility system.