Understanding land use and land cover (LULC) classification is critical for addressing environmental and human needs, particularly in developing countries. Nigeria is a developing country experiencing rapid population growth and economic development leading to increased LULC changes. While many studies have been done on LULC changes, there is a need for a comprehensive review of existing knowledge and limitations of LULC analyses in Nigeria. Hence, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method, this review paper presents a systematic review of LULC analyses in Nigeria by examining the adopted remote sensing data, pre-classified global and regional LULC maps, and classification and validation methods. This paper draws attention to the significant growth in LULC studies and highlights a need for awareness and access to existing and readily available LULC data. This review provides a broad overview of LULC data, classification methods, focus, scale, and constraints associated with LULC analysis in Nigeria. Also, it provides probable solutions to the challenges and GEE-based LULC classification scripts. There is a need to create and prioritize a national LULC data repository to ensure sustainable land monitoring and management in Nigeria. This will facilitate the spatial and temporal assessment of LULC at different scales and regions. High-resolution imagery and advanced classification methods such as deep learning need to be adopted to ensure accurate land cover analysis at different scales. Also, increased awareness programs, collaboration, and capacity-building initiatives will be beneficial to addressing current and emerging challenges related to LULC studies in Nigeria.