Most of the studies tries to predict the COVID-19 parameters in isolation. The current study aims to predict the COVID-19 spread in different regions of India in correlation with weather conditions and air quality index. A data-driven, machine learning based approach is employed for accurate long-term prediction. The accuracy of the model is measured on test data by capturing the regression metrics like R2-Score, RMSE and MAE. Air Quality Index seems to be of least effect on COVID-19 fatalities and COVID-19 cases count is showing an increased trend for the moderate temperature range of 25-40 °C for India. The proposed model is able to predict a long-term prediction (180 days) for COVID-19 cases spread and fatalities. It is also able to correlate the impact of weather Conditions and Air Quality Index on COVID-19 spread.