Accuracy in machine learning classification model (classifier) is a measure of how frequently each classification is correctly deemed positive or negative. Accuracy is calculated by the following mathematical formula
accuracy = (true positives + true negatives) / (all estimated values)
Use the following reference for some good visual examples of accuracy, precision and recall: https://www.evidentlyai.com/classification-metrics/accuracy-precision-recall.