In SVM, the C parameter represents the degree of accuracy in classification that the algorithm must achieve. In short, the C parameter determines how much you want to penalize your model for each misclassified point on a certain curve. A low C smoothens the decision surface, whereas a high C seeks to accurately categorize all training instances by allowing the model to choose more samples as support vectors.