Non-tuberculous mycobacteria (NTM) have been reported to cause pulmonary and extrapulmonary infections. These NTMs are often misdiagnosed as MTB due to their similar clinical presentations to tuberculosis, leading to inappropriate treatment and increased morbidity and mortality rates. This literature review aims to provide an overview of the prevalence, clinical manifestations, diagnosis, and management of NTM infections in Africa. A systematic search was performed using various electronic databases including PubMed, Scopus, and Web of Science. The search was limited to studies published in the English language from 2000 to 2021. The following keywords were used: "non-tuberculous mycobacteria", "NTM", "Africa", and "prevalence". Studies that focused solely on the Mycobacterium tuberculosis complex or those that did not report prevalence rates were excluded. Data extraction was performed on eligible studies. Overall, a total of 32 studies met the inclusion criteria and were included in this review. In our literature review, we identified a total of 32 studies that reported non-tuberculosis mycobacteria (NTM) in Africa. The majority of these studies were conducted in South Africa, followed by Ethiopia and Nigeria. The most commonly isolated NTM species were Mycobacterium avium complex (MAC), Mycobacterium fortuitum, and Mycobacterium abscessus. Many of the studies reported a high prevalence of NTM infections among HIV-positive individuals. Other risk factors for NTM infection included advanced age, chronic lung disease, and previous tuberculosis infection. In conclusion, this literature review highlights the significant burden of non-tuberculosis mycobacteria infections in Africa. The prevalence of these infections is high, and they are often misdiagnosed due to their similarity to tuberculosis. The lack of awareness and diagnostic tools for non-tuberculosis mycobacteria infections in Africa is a major concern that needs to be addressed urgently. It is crucial to improve laboratory capacity and develop appropriate diagnostic algorithms for these infections.