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A histogram serves as the most effective chart for illustrating the frequency of different types of errors encountered with a new application. This is because a histogram is specifically designed to represent the distribution of a dataset. It breaks down continuous data into intervals (or bins) and displays the frequency of data points that fall within each interval.

In the context of monitoring application errors, a histogram allows you to visualize how often each type of error occurs, making it easy to identify patterns or common issues within the application. By employing a histogram, one can quickly assess which errors are most frequent and may need further investigation or remediation.

Control charts serve a different purpose by monitoring process variability over time and determining if a process is in a state of control. While useful for tracking the stability of processes, they do not focus specifically on the frequency of types of errors.

Distribution curves summarize overall data characteristics and show trends, but they may not highlight individual error types as clearly as a histogram.

Gantt charts are utilized for project scheduling and tracking progress over time, making them unsuitable for analyzing error frequencies since they do not represent data distribution or frequency.

Thus, the histogram is the clear choice when it comes to illustrating the frequency of different types of errors encountered with a new application.