<p>Hate speech represents the use of abusive or threatening speech or writing that expresses hatred towards an individual or a particular group based on race, religion, gender, or sexual orientation. The detection of hate speech has become important, as it can increase the crime rate in society. Manual identification of hate speech is a very tedious process, as social media is flooded with an enormous number of posts continuously. There is a notable amount of research in this field considering the English language, but this should also be extended to the Indian languages, as there is only limited research on this, considering the Indian languages. This paper provides a survey on the process associated with hate speech detection and the different methodologies associated with it, considering Indian languages. The survey has also categorized the research work on hate speech detection based on language, extracted features, classification techniques, and the corpus used for the research. The challenges associated with the process are also highlighted, as they can pave the way for further effective research on the detection of hate speech based on Indian languages.</p>