There are complex interactions between the living organisms and the environmental factors in the ecosystems. Understanding the structure and functions of the ecosystems is essential as they are responsible for the maintenance of ecosystem health. The traditional methods of analyzing the various parameters and analyzing them with the statistical methods require lot of time. As there are natural disasters and anthropogenic activities influencing such ecosystems and their biodiversity, conservation measures have to be taken with monitoring, forecasting and control. Machine learning along with sensor network helps in the analysis, monitoring, prediction and forecasting. This paper overviews the application of machine learning models in understanding ecology, species distribution, species identification, biodiversity and conservation. The different types of biodiversity, values and uses of biodiversity, biodiversity at global, national and local levels, hotspots, threats to biodiversity, and conservation of biodiversity are discussed to get an idea about biodiversity and its significance. Use of ML algorithms in biodiversity conservation, challenges and tasks of ML based methods and limitations are dealt with. Various models of Machine learning used in Biodiversity conservation, measurement and prediction of biodiversity, challenges and risks are discussed in detail.